An IoT patient monitoring based on fog computing and data mining: Cardiac arrhythmia usecase

The Internet of Things (IoT), as a new revolution in the digital world, is rapidly expanding in many areas, especially in health care. As IoT devices face challenges in processing and storing information, cloud and IoT integration leads to the development of efficient services and applications. However, one of the big challenges of cloud technology is service delays for remote patients who often require immediate control at different times. Therefore, a new technology called fog computing can be used as an interface between the cloud and end-users to minimize the problem of latency and improve accessibility. On the other hand, heart disease is known to be the second leading cause of death in the world due to various problems in the proper functioning of the heart. One of these problems is cardiac arrhythmia, which can lead to irreparable problems such as heart attack if not diagnosed. One way to diagnose this disease is to make an Electrocardiogram (ECG) from the patient. The purpose of this article is to propose a system for monitoring the health of a patient (a case of cardiac arrhythmia). Arduino's electronic board and AD8232 sensor module were used to test and run the system to monitor heart rhythm and perform electrocardiography. Therefore, the k-Nearest Neighbor (KNN) algorithm, one of the most commonly used data mining algorithms, is used to classify and validate the type of cardiac arrhythmia. (C) 2020 Elsevier B.V. All rights reserved.